This disclosure relates to platoon control of vehicles.
The “background” description provided herein is for the purpose of generally presenting the context of the disclosure. Work described herein, to the extent it is described in this background section, as well as aspects of the description which may not otherwise qualify as prior art at the time of filing, are neither expressly or impliedly admitted as prior art.
Aspects of this disclosure build upon the teachings of the following references, which are referred to throughout:    [1] L. Acar. Boundaries of the receding horizon control for interconnected systems. Journal of Optimization Theory and Applications, 84(2), 1995.    [2] J. T. Betts. Practical Methods for Optimal Control Using Nonlinear Programming. SIAM, 2001.    [3] E. Camponogara, D. Jia, B. H. Krogh, and S. Talukdar. Distributed model predictive control. IEEE Control Systems Magazine, February, 2002.    [4] H. Chen and F. Allgcewer. A quasi-infinite horizon nonlinear model predictive scheme with guaranteed stability. Automatica, 14(10):1205-1217, 1998.    [5] W. B. Dunbar. Distributed Receding Horizon Control of Multiagent Systems. PhD thesis, California Institute of Technology, Pasadena, Calif., 2004.    [6] W. B. Dunbar. Distributed receding horizon control of dynamically coupled nonlinear systems. IEEE Trans. on Automatic Control, 52(7):1249-1263, 2007.    [7] W. B. Dunbar and R. M. Murray. Distributed receding horizon control for multi-vehicle formation stabilization. Automatica, 42(4):549-558, 2006.    [8] P. Falcone, F. Borrelli, E. H. Tseng, J. Asgari, and H. Davor. Low complexity MPC schemes for integrated vehicle dynamics control problems. In Proceedings of the 9th International Symposium on Advanced Vehicle Control (AVEC '08), pages 875-880, 2008.    [9] E. Franco, L. Magni, T. Parisini, M. M. Polycarpou, and D. M. Raimondo. Cooperative constrained control of distributed agents with nonlinear dynamics and delayed information exchange: A stabilizing receding-horizon approach. IEEE Trans. on Automatic Control, 53(1):324-338, 2008.    [10] M. R. Jovanovic and B. Bamieh. On the ill-posedness of certain vehicular platoon control problems. IEEE Transactions on Automatic Control, 50(9):4583-4588, 2005.    [11] T. Keviczky, F. Borrelli, and G. J. Balas. Decentralized receding horizon control for large scale dynamically decoupled systems. Automatica, 42(12):2105-2115, December 2006.    [12] N. J. Kohut, J. K. Hedrick, and F. Borrelli. Integrating traffic data and model predictive control to improve fuel economy. In Proceeding of 12th IFAC Symposium on Control in Transportation Systems, pages 2806-2813, 2009.    [13] Y. Kuwata, A. G. Richards, T. Schouwenaars, and J. P. How. Distributed robust receding horizon control for multi-vehicle guidance. IEEE Transactions on Control Systems Technology, 15(4), July 2007.    [14] Jinfeng Liu, David Munoz de la Pena, and Panagiotis D. Christofides. Distributed model predictive control of nonlinear systems subject to asynchronous and delayed measurements. Automatica, 46(1):52-61, 2010.    [15] D. Q. Mayne, J. B. Rawlings, C. V. Rao, and P. O. M. Scokaert. Contrained model predictive control: Stability and optimality. Automatica, 36:789-814, 2000.    [16] H. Michalska and D. Q. Mayne. Robust receeding horizon control of contrained nonlinear systems. IEEE Trans. Auto. Contr., 38:1623-1632, 1993.    [17] N. Motee and B. Sayyar-Rodsari. Optimal partitioning in distributed model predictive control. In Proceedings of the IEEE American Control Conference, 2003.
The automotive industry is embracing receding horizon control research for powertrain [19] and vehicle stability [8] applications. Furthermore, this research is being applied to path planning applications for autonomous driving [20] and eco-driving [12].
Literature on distributed receding horizon control has examined coupled subsystem dynamics for linear dynamics [1], [3], [17], [23] and nonlinear dynamics [6], [14]. Distributed receding horizon control of multiple decoupled vehicles has also been explored for linear [13], [18] and nonlinear [7], [9], [11] vehicle dynamics, with coupling in cost functions and/or constraints.